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Two approaches were used to interrogate publicly available gene expression data sets, both of which use one or more SNPs (not restricted to lead SNPs) to infer patterns of gene expression based on imputation reference panels (Online Methods).

First, to maximize power, we analyzed data from the largest available e QTL data set for any tissue (whole blood, N = 5,311), under the assumption that some causal genes and regulatory mechanisms might be ubiquitously expressed or functionally involved in blood tissues.

Systematic e QTL integration using the Summary Mendelian Randomization approach to identify tissues and cell types that are enriched for AAM heritability.

Five of the 46 GTEx tissues were positively enriched for AAM-associated variants (Fig. Notably, all of these were central nervous system tissues, including the pituitary, and the hypothalamus was just below the significance threshold for enrichment (P = 9.8 × 10.